Estimating skills changes using LinkedIn Data¶
The data source for the analysis is this IPython notebook is: "World Bank LinkedIn Digital Data for Development" by World Bank Group & LinkedIn Corporation, licensed under CC BY 3.0. More specifically, I use the Public Use - Talent Migration available on the World Bank website.
(The views expressed here are my own)!
Three dimensions of talent migration can be analyzed using LinkedIn data - (i) inter- and intra-country migration; (ii) industry shifts; and (iii) skills changes. When a LinkedIn member's updated job location is different from their former location, the dataset captures this as a physical migration. The industry assignment is based on the industry associated with a member's company on their LinkedIn profile at the time of migration. In this notebook, I only focus on generating insights for the skills dimension for Ghana - a country I am interested in. I begin with an overview of the stock of talent on LinkedIn by skill in Ghana.
Most Ghanaian LinkedIn members have the following skills on their profiles: Digital Literacy; Business Management; Research, and Leadership. By skill category, Business Skills are most common (these include Business Management, Project Management, and People Management). Disruptive Tech Skills (e.g., Data Science, Robotics, etc) are least common. Below I illustrate how the relative frequency of these skills changed between 2015 and 2018.